FAQ: The stream as an interface; starting out in data journalism

Q: What are the advantages of “stream” as an interface for news website homepages?

The main advantages are that it’s very sticky – users tend to leave streams on in the same way that they leave 24 hour news channels on, or keep checking back to Facebook and Twitter (which have helped popularise the ‘stream’ interface).

If you compare that to the traditional story layout format, where users scan across the page but then leave the site if there’s nothing obviously of interest, you can see the difference.

I think there’s room for both, but if you want to know what’s new since the last time you looked, the stream works very well. And it’s not difficult to combine that with subject or region pages that show the most important news of that day, for example.

I think it can work for every kind of news: the stream says ‘Here’s what’s new’ across all topics; the ‘layout’ says ‘Here’s what we think is important’ – in other words, it performs a more traditional ‘snapshot’ function akin to the daily newspaper layout.

2) What are the skills a reporter should have in order to be a top-notch, first-rate data journalist?

The basic skills are the same as any journalist: a nose for a story, and the ability to communicate that clearly. In data journalism terms that means being able to interrogate data quickly and then focus on the most important facts within it.

That will most likely involve being able to use spreadsheet formulae to work out, for example, the proportion of time or money being spent on something, or to combine different datasets to gain new insights or overcome obstacles put in your way by those publishing the data.

You also need to be able to avoid mistakes by cleaning data, for example (often the same person or organisation will be named differently, for example), and by understanding the context of the data (for example, population size, or methodology used to gather it).

Finally, as I say, you need to be able to communicate the results clearly, which often means pulling back from the data and not trying to use it all in your telling of the story (just as you wouldn’t use every quote you got from a source) but keeping it simple.